Sophisticated data management techniques are typically required for large image collections and databases, such as online digital libraries, digital art collections, biomedical imagery, merchandise catalogs, satellite imagery, and fingerprint and mug-shot imagery. The use of such image (data) management systems is necessary in order to efficiently store the image collection and provide content-based searching of the images. The systems assist users to retrieve relevant images based on their content (e.g., specific colors, textures, shapes, etc.).
Traditionally, data compression has been used to efficiently store the images, and a separate indexing structure has been used to permit retrieval of the images. That is, image management systems typically treat compression and indexing as separate entities. For example, the use of inverted files as a separate indexing entity is described in G. Salton, "Introduction to Modern Information Retrieval" (New York, N.Y.: McGraw-Hill, 1983). For further example, the use of signature files as a separate indexing entity is described in I.H. Witten, et al., "Managing Gigabytes: Compressing and Indexing Documents and Images" (New York, N.Y.: Van Nostrand Reinhold, 1994).
The data management systems in which separate indexing entities are used are highly redundant and inefficient, which leads to excessive use of storage space and slow access times. Although compression efficiently represents the data, the separate indexing structure must also be stored. Since a separate indexing structure is redundant and requires additional storage space, the data management system is inefficient. Furthermore, a complete index may be as large as the compressed data, resulting in long search times.